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Diatoms are a very diverse group of microalgae that encompass about 100 000 taxa. This makes an excellent bioindicator especially of rivers. The majority of biotic indices based on diatoms are constructed on species pollution-sensitivities. Nevertheless, recent studies showed the interest to use complementary metrics for biomonitoring: life-forms, cell-sizes and ecological guilds. Unfortunately, taxa memberships to such metrics are scattered in numerous floras and papers. Therefore, studies using such metrics often referred to grey literature or home-made checklists. The objective of this paper is to make available to the scientific community an important check-list of taxa frequently observed in European rivers with their memberships to these metrics. After defining these metrics, 1115 taxa were codified using Biofresh and Omnidia codes in an Excel file. Metrics memberships were then explored in a taxonomical framework. It clearly appears that metrics memberships are determined by taxonomy. Life-forms and cell sizes taxa memberships and their study in the framework of evolutionary history of diatoms is a field that is worth studying for a better understanding of diatoms ecology. Such inputs should be beneficial for the future improvement of diatom-based monitoring tools.

For almost two years (2006–2007), phytoplankton structure and distribution were monitored using a combination of methods in the Marne Reservoir (France). We used the bbe FluoroprobeTM spectrofluorometer, which provides vertical profiles for different algal classes and chlorophyll analysis, based on the in vivo autofluorescence characteristics of the phytoplankton. In parallel, we measured chlorophyll a (chl a) concentrations using the classical extraction method coupled with spectrophotometric analyses, and calculated the biovolume of all the taxa identified using inverted light microscopy. A very close correlation (ρ = 0.93, n = 243, p < 0.0001) was found between the total equivalent chl a concentrations given by the bbe FluoroprobeTM and the total chl a concentrations (g·L−1) provided by the spectrophotometric analysis. The closest correlation was obtained for concentrations below 6.9 μg·L−1 whereas little or no correlation was found for those above 21.6 μg·L−1. The relationship was highly significant when total phytoplankton biovolume was compared with data from the probe (ρ = 0.6, n = 243, p < 0.0001), the strongest correlation being found for the group composed of diatoms, dinoflagellates and chrysophyceae (ρ = 0.67, p < 0.0001), while the weakest relationship was for the blue-green cyanobacteria (ρ = 0.33, p < 0.0001), although it was still highly significant. Our analysis, based on a large dataset, indicates that the FluoroprobeTM appears to be a reliable tool suitable for use by fresh water managers to monitor phytoplankton on any relevant time and space scales.

Biomonitoring is central to the European Union's Water Framework Directive (WFD) and to the French water and aquatic environmental law, but most diatom indices do not separate different anthropogenic impacts. To address this gap, the effect of water chemistry on diatom ecological guilds and life forms was assessed in order to indicate stream perturbations. Generalised additive models (GAMs) were built on a large-scale data set of 1571 samples from the French monitoring network. The relationships between diatom ecological guild and life form metrics were investigated by Principal components analysis and the results predicted by GAMs. The models characterised eight chemical parameters that modified adaptive strategies (ecological guilds) and growth morphology (life forms). Total phosphorus, conductivity, nitrate and pH are the main influencing factors, followed by temperature, dissolved oxygen and organic matter. The findings confirm three groups of diatoms with different adaptive strategies: 1 – fast moving species, 2 – species growing close to the substrate and 3 – species extending to the surface layers of the biofilm. Thirteen diatom metrics displayed a variety of responses to different ranges of the eight chemical parameters. These metrics could be used to help to identify and quantify which chemical alterations are caused by polluted effluents in rivers.